Analytics Dashboard

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Problem Summary

Users need a concise, high-level overview of a complex set of information, usually focusing on key metrics, that represents the status of important organizational entities, processes, or activities as a means of determining potential areas that may require investigation or intervention.

Usages

An analytics dashboard is used when:
• Information related to a particular organizational function or role needs to be monitored regularly, possibly in real time.
• The information sources represent critical metrics that must be understood at a glance.
• The information sources are diverse and complex, requiring some degree of summarization or aggregation to be comprehensible.
• Deviations from expected or desired values or thresholds are of particular importance and require immediate investigation or action.
• The optimal selection of key information and data is specific to a particular individual or role (or may be customized by the end user).
• A view of the overall trends for key metrics is required, providing visibility into the relationship between key values and trends.
• Users need access to the above functionality without being obliged to build a complex query.
• Users need access to the above functionality without being obliged to undergo extensive training or familiarization with the system.

Constraints and Challenges

• The selection of a particular default set of metrics and content may not be optimal for all users.
• The presentation of high-level summaries may limit the initial visibility of certain lower-level metrics.
• Presenting the key information and data within a finite screen space may require the omission of some metrics.
• Reliability of real-time updates and/or related latency issues may compromise the effectiveness of the dashboard.
• Meaningful time frames for summarization and analysis may vary among key metrics.

Solution Elements

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Identify the primary user segment(s) that will be served by the dashboard and develop an appropriate strategy for dealing with variation among those users.
- For example, a consistent, homogeneous user group may be well served by a common dashboard design, but a heterogeneous group of users with varying roles and goals may need to be provided with some degree of end user personalization or customization. [Note that a full examination of techniques and UI patterns for end user customization is beyond the scope of this pattern.]
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Identify the data and metrics that are most relevant to the priority user segment(s). Organize the content and dashboard elements into meaningful groups so that connections between related elements are immediately apparent.
- Use the Gestalt principles of organization (e.g., proximity, closure, continuation, similarity, etc.) to reinforce these connections. [Note that a full examination of techniques and patterns for creating meaningful content groups is beyond the scope of this pattern.]
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Use size, position, orientation, etc., to indicate the relative importance of each content element.
- Color and other decorative treatments can also be applied to highlight certain elements and thus indicate relative importance, but these should be used sparingly (and also have accessibility implications -- see below).
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Optional: Consider placing the most important elements front and center; this may increase visibility for most users.
- Additionally, consider placing the most important elements to align with the reading direction of the prevailing culture, e.g., top left for cultures that use a left-to-right reading direction.
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Distill and condense key information and data through the use of summaries and overviews.
- Minimize information overload by focusing on what is currently happening, rather than the why or how.
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Make the information summaries and metrics interactive and actionable where possible, so that the transition from perception of an issue to the action required to investigate or resolve it is as seamless as possible.

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Where further levels of detail exist, complement the information summaries with the ability to drill down into more detailed information

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Draw attention to exceptions or important changes so that the user can gain immediate visibility into deviations from expected or desired values.
- For example, use locally recognizable color conventions to show "negative" exceptions or deviations (e.g., red text, red icons, etc.).
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Clearly differentiate between those elements that are of continuous relevance or interest (such as key summary metrics and trends) and those that are ephemeral in nature and may require more immediate and focused investigation and action (such as alerts and updates).
- Develop a consistent design treatment that reinforces these differences.
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Ensure that the key information and content is displayed on a single screen, so that the user can gain an immediate overview without needing to scroll or otherwise interact with the data.
- If the page itself extends beyond a single screen, ensure that the key information is visible above the fold.
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Select UI elements to maximize the effective communication of information and enable the user to quickly and intuitively grasp key data points, relationships, patterns, and trends.
- For example, use summary visualizations (e.g., graphs for trends and patterns in quantitative information; gauges for simple measures and/or comparison with expected values; icons for alerts and simple status messages).
- [Note that a full examination of techniques and UI patterns for selecting appropriate display mechanisms is beyond the scope of this pattern.]
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Provide visible and meaningful reference points and benchmarks to provide context that enables users to draw comparisons to evaluate the status and meaning of data points and visualizations of key metrics.

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Provide clear indicators of the default time frames applied for varied dashboard elements (e.g., time spans) and the freshness/recency of the information (e.g., date/time of updates).
- When relevant and useful, enable users to modify the time span for a specific dashboard element of related group of elements -- when doing so, use appropriate UI frames, principles of visual organization, and UI text labels/feedback to convey the impact of changing time frames on the dashboard elements.
- Align default time frames and update parameters with user scenarios, mental models, and the expected/desired ebb and flow of user action.
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Exercise caution when using metaphorical elements such as radial gauges or linear meters.
- Although such metaphors may have a superficial aesthetic appeal, this is not always reflected in their usefulness or usability. The primary concern should always be the degree to which the chosen display method effectively communicates its current status or value.
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Cautions

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An over-reliance on metaphorical display mechanisms (e.g. radial gauges, etc.) can compromise usability and readability.

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Rationale

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A well-designed dashboard allows end users to make better decisions by maximizing the visibility of relevant organizational information and data, thus saving time and increasing productivity.

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Related Patterns

Breadbox

Analytics Dashboard

Problem Summary

Usages

Constraints and Challenges

Solution Elements

Identify the primary user segment(s) that will be served by the dashboard and develop an appropriate strategy for dealing with variation among those users.

Identify the data and metrics that are most relevant to the priority user segment(s). Organize the content and dashboard elements into meaningful groups so that connections between related elements are immediately apparent.

Use size, position, orientation, etc., to indicate the relative importance of each content element.

Optional: Consider placing the most important elements front and center; this may increase visibility for most users.

Distill and condense key information and data through the use of summaries and overviews.

Make the information summaries and metrics interactive and actionable where possible, so that the transition from perception of an issue to the action required to investigate or resolve it is as seamless as possible.

Where further levels of detail exist, complement the information summaries with the ability to drill down into more detailed information

Draw attention to exceptions or important changes so that the user can gain immediate visibility into deviations from expected or desired values.

Clearly differentiate between those elements that are of continuous relevance or interest (such as key summary metrics and trends) and those that are ephemeral in nature and may require more immediate and focused investigation and action (such as alerts and updates).

Ensure that the key information and content is displayed on a single screen, so that the user can gain an immediate overview without needing to scroll or otherwise interact with the data.

Select UI elements to maximize the effective communication of information and enable the user to quickly and intuitively grasp key data points, relationships, patterns, and trends.

Provide visible and meaningful reference points and benchmarks to provide context that enables users to draw comparisons to evaluate the status and meaning of data points and visualizations of key metrics.

Provide clear indicators of the default time frames applied for varied dashboard elements (e.g., time spans) and the freshness/recency of the information (e.g., date/time of updates).

Exercise caution when using metaphorical elements such as radial gauges or linear meters.

Cautions

An over-reliance on metaphorical display mechanisms (e.g. radial gauges, etc.) can compromise usability and readability.

Rationale

A well-designed dashboard allows end users to make better decisions by maximizing the visibility of relevant organizational information and data, thus saving time and increasing productivity.

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